In an electric utility, there are usually several systems that maintain and/or utilize data representing the structure of the electrical network. These systems may include, without limitation, Geographic Information Systems (GIS), Design Systems, CAD Systems, Asset Management Systems, SCADA Systems, Outage Management Systems (OMS), Distribution Management Systems (DMS), and Energy Management Systems (EMS)
Some of these components may be “homegrown” within a utility, while others are likely to be commercially available products, or site-specific implementations based on such products. Model management is a term that may be used to refer to the processes associated with maintaining consistency between network representations stored by these various systems and the real-world network.
Clearly, model management is about integration and synchronization. Previous efforts have been made to integrate existing OMS and DMS product offerings. One area in which it is expected that previous experiences can be leveraged to improve energy management and control systems, such as an OMS/DMS, is that of GIS Data Integration. For example, it would be desirable to develop the ability to accept network data from an external GIS to populate the operational OMS/DMS thus reducing the time and effort to set up and deploy an OMS/DMS.
It is recognized that in many deployments, such integration would require the transformation of network information from a geographic to a schematic form. In this case, the chosen path for integration between systems was the IEC TC57 WG13 and WG14 61968 61970 model. This is simply referred to as the CIM model and is a standard for exchanging the electrical network between systems. The data is both initial load and incremental updates to the network as distribution networks change frequently.
It would be advantageous, therefore, to provide a methodology of managing a large-scale normal state network model from the electric power transmission and distribution domain. It would be further advantageous to provide a methodology wherein frequently changed normal state network data can be stored and version controlled so that the data may be conveniently used by other applications.